Creme Collective — Meeting Update

Data Analytics & Automation | Recurring Meeting
April 27, 2026 Jeremy Triefenbach, Leilah Mundt, Daniel Castro, Annie Severn, Diego Sanz Jira: CC-377
Overview
Recurring Sync — April 27, 2026

Meeting Summary

Jeremy announced a 3-month priority pivot: warehouse efficiency replaces portal feature development as the primary focus. The data and automation opportunity is significant — Daniel Castro estimates 30% of the team is dedicated to mundane admin tasks, with a target of 5–10%. Portal work continues at a maintenance pace (first client onboarding, no new features yet). Two new Jira items created: Warehouse Efficiency epic (CC-378) and Labor Management Report (CC-379).

1
Resolved
4
In Progress
3
New / Discussion
Resolved
Closed This Week

Analytics Portal — 503 Error (Fixed)

CC-376 · Done
What happened

All analytics pages at creme-portal.datastudios.ai/admin/analytics/* returned 503 errors after the CC-368 deploy triggered a restart of the portal service. Root cause: two bugs shipping together in CC-363 — (1) a hardcoded creme-collective AWS profile fallback that doesn't exist on the EC2 instance, and (2) a missing IAM permission for the creme-analytics/rds-password secret.

Resolution

Both bugs fixed: code updated to fall through to the instance role credential chain when AWS_PROFILE is unset, and the IAM policy on creme-whisper-dev updated to allow the analytics RDS secret. All four analytics report paths confirmed operational in production. Confirmed during this meeting.

In Progress
Active Work

Crème AI Agents

CC-317 · In Progress
Background

Three agent concepts have been identified through conversations with Danny, Andrea, and Tyler. These directly support the warehouse efficiency pivot: automation of high-volume, low-value administrative tasks currently consuming significant team time.

Discussed this meeting

Three agent scopes confirmed:

  • Warehouse agent (Danny) — EDI data entry across systems, order closing, billing admin. Danny is documenting current processes via Chat for Diego to synthesize before scheduling deep-dive calls.
  • Sales agent (Tyler) — Automates prompting salespeople to enter field notes for monthly reports. Eliminates delay risk from individual absence (Tyler's absence pushed back the March dry run).
  • Accounting agent (Andrea) — Invoice automation via QuickBooks. Daily shipment files already live; QB import + send is the next phase (see CC-290).
Next Steps
  • [Diego] Synthesize Danny's process documentation, then schedule one-on-one deep-dive calls to fill gaps.
  • [Daniel Castro] Continue documenting warehouse processes (order closing, billing, EDI) via Chat tools.

HubSpot → Internal CRM Migration

CC-342 · In Progress
Background

Full migration from HubSpot to the internal CRM (portal). HubSpot subscription ends in September, which sets the hard cutover deadline. The sales team is small and manageable for training.

Progress

Significant data migrated from HubSpot, including the brand vs. store matrix. Plan: run HubSpot and the internal CRM in parallel for the next 3–4 months to build confidence, with full cutover in September. The April report dry run will include a fresh import of data into the internal CRM, simulating a full cutover.

Next Steps
  • [Leilah] Communicate training dates and cutover timeline to the sales team.
  • [Diego] Execute April dry run import and CRM simulation with Tyler and Darcy.

Monthly Client Report & Field Notes App

CC-343 · In Progress
Background

Monthly client report migrated from PDF/Tableau to portal. Field Notes app built — records audio updates from sales team in the field, auto-transcribes, categorizes, and summarizes for CRM submission. The March dry run was delayed due to Tyler's absence.

Progress

Data for the March report is aligned with the manually generated report already sent to clients. Only the notes section and the pipeline report attachment remain to be added. Gmail → CRM thread integration is also live. Rollout plan confirmed:

  • April dry run — Limited set (Tyler + Darcy) this week, fresh CRM import, simulate full cutover.
  • June/July — Basic report rolled out to all clients. Wonder Valley confirmed as first beta client for the portal view.
  • Portal view — Delivered alongside the PDF email; clients can filter and interact with data. Wonder Valley gets the full transparent view; other clients get the basic report.
Next Steps
  • [Leilah] Coordinate with Tyler and Darcy this week — QA the Field Notes app and confirm the April dry run plan.
  • [Leilah] Schedule a 30-minute follow-up call with Diego later this week.
  • [Diego] Send Leilah login credentials and link for the client portal mockup.

Invoicing & Shipping Automation

CC-290 · In Progress
Background

Andrea's invoicing process is highly manual — Camelot data pull, Excel cleanup, and line-by-line QuickBooks entry. Discussed in the April 2 meeting; Phase 1 (daily shipment files to Google Drive) was the initial target.

Progress

Daily automated shipment files by brand are live in Google Drive. The next phase is automating the QuickBooks import and invoice generation, requiring only Andrea's final approval to send. Leilah confirmed Andrea's processes are a high-value target and should be prioritized after the monthly report and Danny's warehouse work.

Next Steps
  • [Diego] Continue QuickBooks API integration — automate invoice creation and send pipeline (Phase 2).
New / Discussion
New Initiatives & Topics Raised

Warehouse Efficiency — 3-Month Priority Pivot

CC-378 · New Epic
Strategic decision

Jeremy announced a pivot: for the next 3 months, warehouse operations efficiency replaces the portal feature roadmap as the primary focus. The driver is leverage — as volume scales, every extra step requires manual effort with no compounding return. Doubling volume currently doubles all manual work. Portal development continues at maintenance pace (bug fixes, first client onboarding) but no new features.

Four efficiency buckets identified
  • Labor management — Track hours by activity type (e-commerce orders, PR kits, receipts) to enable Danny to schedule staffing efficiently. Currently takes 2 hours of manual work to pull 6 weeks of data.
  • Admin / data entry — 30% of team currently dedicated to mundane admin tasks; target is 5–10%. Warehouse staff scan items then must manually re-enter data into systems — the same work done twice.
  • EDI process — Tracking details must be entered into 3 separate systems (retailer TMS, EDI system, billing system) for every order. Target: automate 80%+ of this data entry.
  • AI customer service — Automate boilerplate inquiries (tracking codes, order status) via an AI agent, reducing burden on customer service staff.

Strategy: survey key team members to map where time is spent on manual tasks. Diego to synthesize Danny's process documentation and begin systematic deep dives.

Next Steps
  • [Diego] Reach out to Danny for a deep dive into warehouse automation processes.
  • [Diego] Assess current time/payroll system — evaluate Gusto replacement feasibility for capturing labor hours.
  • [Diego] Prepare acceleration proposal with required resources, costs, and revised project deadlines (targeting fall readiness for Q4).
  • [Daniel Castro] Continue full-download process documentation via Chat.

Labor Management Report

CC-379 · New Story
What was requested

Jeremy identified the labor management report as the first concrete deliverable under the warehouse efficiency initiative. Currently, populating 6 weeks of operational data requires 2 hours of Danny's manual effort. The report should make this data automatically available and up-to-date.

Scope defined

Track operational hours by activity type: e-commerce orders, PR kits, receipts, and other warehouse activities. When live, Danny can:

  • See current activity volumes and staff hour commitments at a glance.
  • Forecast staffing needs (“I don’t need 20 hours this week” vs. “big batch incoming”).
  • Eventually compare labor hours against order volumes and client fees to get P&L visibility at the warehouse level — a key input for pricing decisions.

Jeremy also suggested this data could eventually replace the current external payroll time system (Gusto), giving Creme full ownership of labor data.

Next Steps
  • [Diego] Build the labor management report — identify source data (Camelot, Sage, or manual input), define KPIs, determine delivery format.
  • [Diego] Assess Gusto replacement feasibility as part of the labor data strategy.
  • [Daniel Castro] Confirm data fields available for labor hour tracking from existing systems.

AI Transformation & Partnership Discussion

Discussion · No ticket
Topic raised

Diego introduced the concept of a deeper collaboration or formal partnership between DataStudios and Creme Collective around AI transformation. Creme’s profile as a service-based, operations-intensive company is particularly well-suited for building AI-powered platforms and services at scale.

Discussion outcome

Leilah described the alignment as “so obvious and perfect.” Key themes discussed:

  • The intelligence portal as a potential white-labeled product for other clients in similar industries.
  • Creme as a proving ground and co-builder for AI-driven operational platforms.
  • Capacity and retainer discussion — Diego confirmed ability to scale with augmented staff; acceleration to June (vs. July) for the monthly report rollout is achievable with increased commitment.
  • Long-term vision: Creme reaches a point of Q4 readiness where efficiency gains allow scaling without proportional headcount growth — a compelling narrative for future investors.
Next Steps
  • [Diego] Prepare a follow-up proposal covering: ideas for the partnership structure, financial expectations, project timing, and potential deadlines.
  • [Diego] Schedule a follow-up conversation with Leilah to present the proposal.

Notes by Gemini — reviewed and published to DataStudios doc portal. · CC-377